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According to the increasing safety and reliability requirements of all electric / more electric aircraft, the reliable operation of electro-hydraulic actuator with variable pump and variable motor (EHA-VSVP) is very important. As a complicate mechanical-electro-hydraulic integration system, EHA-VSVP has complex fault features and symptoms; a novel fault diagnosis method based on the grey relation...
This paper presents a fault diagnosis method for power transformer. Fault diagnosis plays an importance role in the efforts for transformer diagnosis to shift form “preventive maintenance” to “condition based maintenance” (CBM), and consequently to reduce the maintenance cost. Ever since its birth, numerous techniques have been researched in this field, each method however, has its own advantages...
In view of the bridge structure monitor signal type and the distribution characteristic, has designed and constructed a high performance distributed data acquisition system for bridge health monitoring. The system topology uses the double ring network of optical fiber, and has designed the acquisition software flow, analysis department entirely failure diagnosis, the acquisition time synchronization...
Decision rules of fault diagnosis were acquired after analyzing the inconsistent fault information system. By converting inconsistent information system into a consistent one based on the application of generalized decision function of inconsistent information system of rough sets and then by reducing the condition attributes of fault diagnosis based on the compatible relation of rough sets, relative...
For the system of vibration faults diagnosis of hydraulic turbines, the deficiency of generalization ability using single BP Network is analyzed and a radial basis function (RBF) neural network algorithm based on particle swarm optimization (PSO) is presented. It has advantage of being easy to realize, simple operation and profound intelligence background. The parameters and connection weight are...
Transformer faults are quite complicated phenomena and can occur due to a variety of reasons. There have been several methods for transformer fault synthetic diagnosis, but each of them has its own limitations in real fault diagnosis applications. In order to overcome those shortcomings in the existing methods, a new transformer fault diagnosis method based on a wavelet neural network optimized by...
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